Operations | Monitoring | ITSM | DevOps | Cloud

Seer: debug with AI at every stage of development

When we launched Seer, our AI debugging agent, we built it on a core belief: production context is essential for understanding the complex failure modes of real-world software. Seer uses the detailed telemetry that Sentry collects (errors, spans, logs, metrics, and more) to accurately root cause and fix bugs. Because this telemetry is trace-connected, Seer can deterministically traverse all the data relevant to a problem rather than relying exclusively on imprecise time-range searches.

How to Reduce Service Desk Workload with AI and Automation

For many IT directors, the service desk feels permanently stretched. It’s a math problem that is forever in motion. Every quarter brings new apps, new devices, new access rules, and new ways for small issues to become daily interruptions. Even when tooling improves, the queue still grows because the work expands with the environment. The pressure shows up in familiar places, like rising ticket counts, tighter SLAs, and a large backlog of projects that need help.

The 2026 IT Leader's Priority Shift: Why AI, Resilience, and Visibility Now Outrank Everything Else

IT leaders are replacing traditional focuses with three things that now outrank everything else: AI readiness, operational resilience, and unified visibility. You can’t add another priority to the list. There’s no space left. Your team is already stretched managing hybrid infrastructure, responding to incidents, juggling tool sprawl, and delivering on AI promises while keeping costs under control.

Getting Started with Seer - Sentry's AI Debugging Agent

Seer is Sentry's AI Debugging agent that has access to all the context that Sentry pulls together from your applications. Sometimes it shows up predicting bugs before they ship to prod. Sometimes it's catching issues in prod and bringing you the fix. Seer pulls from distributed traces, logs, profiles, stack traces, errors, and your codebase, and helps you find the broken parts of your application and fix them faster.

AI Is WAY More Expensive Than You Think... | SolarWinds TechPod #105

Artificial intelligence isn’t just about innovation and efficiency — it comes with hidden costs. From massive data centers and rising energy consumption to layoffs, governance, and long-term business impact, the real price of AI is often ignored. Companies rush to adopt AI, but are they calculating the true cost for the environment and their bottom line?

Optimize your CI/CD pipeline with CircleCI Chunk AI agent

A slow CI/CD pipeline costs more than just time. Developers context-switch while waiting for builds, feedback loops stretch longer, and compute costs add up with every inefficient run. Most teams know their pipelines could be faster, but optimizing configurations requires deep knowledge of caching strategies, parallelism, and resource allocation. The challenge compounds with AI-assisted development. As AI coding assistants help teams ship code faster, pipelines run more frequently.

Refactor your codebase with CircleCI Chunk AI agent

d function there, and before long you’re navigating a codebase full of inconsistent patterns, repeated logic, and code that’s harder to maintain than it should be. Refactoring is essential, but finding the time to clean up code while shipping features is a constant challenge. The rise of AI-assisted development has accelerated this tension. AI coding assistants help teams ship features faster, but they don’t always produce consistent code.

Can We Still Trust the Code? #speedscale #qualityassurance #digitaltwin #trust #devops

The "Velocity Gap" is real. AI like Claude and GitHub Copilot are pumping out code faster than ever, but there’s a catch: Engineers don't trust it yet. We’re moving away from the old days of "clicking around" in a test environment, but how do we verify code at the speed of light? Ken breaks down why the future of QA isn't just "testing," it’s simulation. Video collab with @ScottMooreConsultingLLC Learn More: speedscale.com.

The 4 pillars of AI in 2026: Agents, cost, observability & sovereignty

AI is no longer just about "one-shot" prompts. In this session from our "From Idea to Agent" webinar, Ben Norris (AI Engineer at Civo) breaks down the four key priorities dominating the enterprise space in 2026. From the 130x explosion in token usage to the "vibe-coding" revolution, learn why businesses are turning away from US hyperscalers in favor of democratized, secure, and UK-sovereign AI infrastructure. We explore how autonomous agents are solving multi-step problems and why "Chain of Thought" reasoning is unlocking AI for heavily regulated industries like finance and healthcare.